Google: An AI-First Company

recent results indicate that machine learning, powered by “neural nets” that emulate the way a biological brain operates, is the true path towards imbuing computers with the powers of humans, and in some cases, super humans.

As Pedro Domingos, author of the popular ML manifesto The Master Algorithm, writes, “Machine learning is something new under the sun: a technology that builds itself.” Writing such systems involves identifying the right data, choosing the right algorithmic approach, and making sure you build the right conditions for success. And then (this is hard for coders) trusting the systems to do the work.

While machine learning won’t replace humans, it will change humanity.

Machine learning requires a different mindset. People who are master coders often become that way because they thrive on the total control that one can have by programming a system. Machine learning also requires a grasp of certain kinds of math and statistics, which many coders, even gonzo hackers who can zip off tight programs of brobdingnagian length, never bothered to learn.

It also requires a degree of patience. “The machine learning model is not a static piece of code — you’re constantly feeding it data,” says Robson. “We are constantly updating the models and learning, adding more data and tweaking how we’re going to make predictions. It feels like a living, breathing thing. It’s a different kind of engineering.”

“It’s a discipline really of doing experimentation with the different algorithms, or about which sets of training data work really well for your use case,” says Giannandrea, who despite his new role as search czar still considers evangelizing machine learning internally as part of his job. “The computer science part doesn’t go away. But there is more of a focus on mathematics and statistics and less of a focus on writing half a million lines of code.”